Month: January 2016

In this thesis many risk-based asset allocation models are compared, focusing particularly on the Risk Parity strategy. Risk Parity is an allocation method used to build diversified portfolios that does not rely on any assumptions of expected returns, thus placing

A simple task: use machine learning in order to avoid useless local searches to be started. Try to find new putative optimal configurations learning from past trials. Skill required: just python – most numerical experiments in circle packing have already been

The aim of this thesis is to obtain a Trust-Region algorithm to solve Generalized Nash Equilibrium Problems (GNEPs). The requested properties of the method are both global and local fast convergence, which have to be achieved under local Error

Training an SVM when many (most) data are unlabeled. This thesis considers an approach based on a continuous differentiable formulation of the problem. Candidate: Andrea Boddi Start: January 2016 Image credits: http://inverseprobability.com/ncnm/